arXiv subjects

Samir Bennani

Publications and source records attributed to Samir Bennani.

16 recordsLinked to original sources

arXiv2024

European Satellite Benchmark for Control Education and Industrial Training

To overcome the innovation gap of the Guidance, Navigation and Control (GNC) design process between research and industrial practice a benchmark of industrial relevance has been developed and is presented. This initiative is driven as well by the necessity to train future GNC engineers and the GNC space community on a set of identified complex problems. It allows to demonstrate the relevance of state-of-the-art modeling, control and analysis algorithms for future industrial adoption. The modeling philosophy for robust control synthesis, analysis including the control architecture that enables the simulation of the mission, i.e. the acquisition of a high pointing space mission, are provided.

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arXiv2023

Launcher Attitude Control based on Incremental Nonlinear Dynamic Inversion: A Feasibility Study Towards Fast and Robust Design Approaches

The so-called ``New Space era'' has seen a disruptive change in the business models and manufacturing technologies of launch vehicle companies. However, limited consideration has been given to the benefits that innovation in control theory can bring; not only in terms of increasing the limits of performance but also reducing mission preparation or ``missionisation'' efforts. Moreover, there is a gap between the current state-of-practice that still relies on linear controls and other modern control techniques that could bring relevant improvements in launcher attitude control. Nonlinear Dynamic Inversion (NDI) is a technique that basically `cancels' the nonlinearities of a class of nonlinear systems, allowing for a single linear control law to be applied without the need for gain-scheduling across different operational points. Incremental NDI (INDI) is a variation of NDI that generates incremental commands and employs acceleration feedback to reduce model dependency, making it easier to design, and results in being more robust in closed-loop. While INDI has been applied successfully to several aerospace applications, its applicability to launch vehicles has not yet been adequately investigated. The objective of this paper is therefore to introduce and raise awareness of the INDI method among the launcher guidance, navigation, and control (GNC) community, showcasing its implementation on a representative launch ascent application scenario which highlights INDI's strengths and challenges. We present a new, practical approach for stability analysis of INDI for attitude control, and compare INDI with scheduled PD controllers with- and without angular acceleration estimates. Results show that, while INDI controllers are generally more sensitive to sensor noise and actuator delay than linear controllers, their potential benefits outweigh these limitations in terms of robustness and performance.

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arXiv2023

Robust Optimal Control for Nonlinear Systems with Parametric Uncertainties via System Level Synthesis

This paper addresses the problem of optimally controlling nonlinear systems with norm-bounded disturbances and parametric uncertainties while robustly satisfying constraints. The proposed approach jointly optimizes a nominal nonlinear trajectory and an error feedback, requiring minimal offline design effort and offering low conservatism. This is achieved by decomposing the affine-in-the-parameter uncertain nonlinear system into a nominal $\textit{nonlinear}$ system and an uncertain linear time-varying system. Using this decomposition, we can apply established tools from system level synthesis to $\textit{convexly}$ over-bound all uncertainties in the nonlinear optimization problem. Moreover, it enables tight joint optimization of the linearization error bounds, parametric uncertainties bounds, nonlinear trajectory, and error feedback. With this novel controller parameterization, we can formulate a convex constraint to ensure robust performance guarantees for the nonlinear system. The presented method is relevant for numerous applications related to trajectory optimization, e.g., in robotics and aerospace engineering. We demonstrate the performance of the approach and its low conservatism through the simulation example of a post-capture satellite stabilization.

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arXiv2023

Robust Nonlinear Optimal Control via System Level Synthesis

This paper addresses the problem of finite horizon constrained robust optimal control for nonlinear systems subject to norm-bounded disturbances. To this end, the underlying uncertain nonlinear system is decomposed based on a first-order Taylor series expansion into a nominal system and an error (deviation) described as an uncertain linear time-varying system. This decomposition allows us to leverage system level synthesis to jointly optimize an affine error feedback, a nominal nonlinear trajectory, and, most importantly, a dynamic linearization error over-bound used to ensure robust constraint satisfaction for the nonlinear system. The proposed approach thereby results in less conservative planning compared with state-of-the-art techniques. We demonstrate the benefits of the proposed approach to control the rotational motion of a rigid body subject to state and input constraints.

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arXiv2022

Asynchronous Computation of Tube-based Model Predictive Control

Tube-based model predictive control (MPC) methods bound deviations from a nominal trajectory due to uncertainties in order to ensure constraint satisfaction. While techniques that compute the tubes online reduce conservativeness and increase performance, they suffer from high and potentially prohibitive computational complexity. This paper presents an asynchronous computation mechanism for system level tube-MPC (SLTMPC), a recently proposed tube-based MPC method which optimizes over both the nominal trajectory and the tubes. Computations are split into a primary and a secondary process, computing the nominal trajectory and the tubes, respectively. This enables running the primary process at a high frequency and moving the computationally complex tube computations to the secondary process. We show that the secondary process can continuously update the tubes, while retaining recursive feasibility of the primary process.

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arXiv2022

Reconfiguration of a satellite constellation in circular formation orbit with decentralized model predictive control

Satellite constellation missions, consisting of a large number of spacecraft, are increasingly being launched or planned. Such missions require novel control approaches, in particular for what concerns orbital phasing maneuvers. In this context, we consider the problem of reconfiguration of a satellite constellation in a circular formation. In our scenario, a formation of equally spaced spacecraft need to undergo an autonomous reconfiguration due to the deorbiting of a satellite in the formation. The remaining spacecraft have to reconfigure to form again an equidistant formation. To achieve this goal, we consider two decentralized strategies that rely on different sets of information about the neighboring spacecraft in the formation. In the fully decentralized case, each controller knows only the current states of each spacecraft, i.e. position and velocity, while in the second decentralized strategy with with information sharing, the entire planned nominal trajectory of each spacecraft is available to its neighbors. Our numerical simulation results show that, by increasing the amount of information available to each spacecraft, faster reconfiguration maneuvers with smaller fuel consumption can be achieved.

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arXiv2021

Finite Horizon Worst-Case Analysis of Linear Time-Varying Systems Applied to Launch Vehicle

This paper presents an approach to compute the worst-case gain of the interconnection of a finite time horizon linear time-variant system and a perturbation. The input/output behavior of the uncertainty is described by integral quadratic constraints (IQCs). A condition for the worst-case gain of such an interconnection can be formulated using dissipation theory as a parameterized Riccati differential equation, which depends on the chosen IQC multiplier. A nonlinear optimization problem is formulated to minimize the upper bound of the worst-case gain over a set of admissible IQC multipliers. This problem can be efficiently solved with a custom-tailored logarithm scaled, adaptive differential evolution algorithm. It provides a fast alternative to similar approaches based on solving semidefinite programs. The algorithm is applied to the worst-case aerodynamic load analysis for an expendable launch vehicle (ELV). The worst-case load of the uncertain ELV is calculated under wind turbulence during the atmospheric ascend and compared to results from nonlinear simulation.

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arXiv2021

System Level Disturbance Reachable Sets and their Application to Tube-based MPC

Tube-based model predictive control (MPC) methods leverage tubes to bound deviations from a nominal trajectory due to uncertainties in order to ensure constraint satisfaction. This paper presents a novel tube-based MPC formulation based on system level disturbance reachable sets (SL-DRS), which leverage the affine system level parameterization (SLP). We show that imposing a finite impulse response (FIR) constraint on the affine SLP guarantees containment of all future deviations in a finite sequence of SL-DRS. This allows us to formulate a system level tube-MPC (SLTMPC) method using the SL-DRS as tubes, which enables concurrent optimization of the nominal trajectory and the tubes, while using a positively invariant terminal set. Finally, we show that the SL-DRS tubes can also be computed offline.

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arXiv2021

Optimal Science-time Reorientation Policy for the Comet Interceptor Flyby via Sequential Convex Programming

This paper introduces an algorithm to perform optimal reorientation of a spacecraft during a high speed flyby mission that maximizes the time a certain target is kept within the field of view of scientific instruments. The method directly handles the nonlinear dynamics of the spacecraft, sun exclusion constraint, torque and momentum limits on the reaction wheels as well as potential faults in these actuators. A sequential convex programming approach was used to reformulate non-convex pointing objectives and other constraints in terms of a series of novel convex cardinality minimization problems. These subproblems were then efficiently solved even on limited hardware resources using convex programming solvers implementing second-order conic constraints. The proposed method was applied to a scenario that involved maximizing the science time for the upcoming Comet Interceptor flyby mission developed by the European Space Agency. Extensive simulation results demonstrate the capability of the approach to generate viable trajectories even in the presence of reaction wheel failures or prior dust particle impacts.

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arXiv2021

Autonomous parafoil precision landing using convex real-time optimized guidance and control

To overcome the limitations of current parafoil precision landing capabilities, an efficient real-time convex optimized guidance and control strategy is presented. Successive convexification of the parafoil guidance problem guarantees local optimality with polynomial convergence rate for efficient real-time implementation, where each iteration is dynamically feasible. Our approach shows reliable and fast numerical convergence through in-flight recalculation of time of flight and a new optimal trajectory to cope with time-varying dynamics. The efficiency of our strategy is demonstrated via a comparative analysis of the existing X-38 in-flight demonstrated guidance and control system. Exhaustive Monte-Carlo simulations show performance improvements of about one order of magnitude. The concept proposed is simple, yet general, as it scales to any atmospheric parafoil landing system and allows efficient implementation relying only on the turn rate information.

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arXiv2021

A System Level Approach to Tube-based Model Predictive Control

Robust tube-based model predictive control (MPC) methods address constraint satisfaction by leveraging an a priori determined tube controller in the prediction to tighten the constraints. This paper presents a system level tube-MPC (SLTMPC) method derived from the system level parameterization (SLP), which allows optimization over the tube controller online when solving the MPC problem, which can significantly reduce conservativeness. We derive the SLTMPC method by establishing an equivalence relation between a class of robust MPC methods and the SLP. Finally, we show that the SLTMPC formulation naturally arises from an extended SLP formulation and show its merits in a numerical example.

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arXiv2018

Model Based Desgin Environment for Launcher Upper Stage GNC Development

The cost associated with developing flight control forms a significant part of the overall development cost. The increased demand for greater functionality and for extending the domain of applicability of future launchers leads to higher complexity of the GNC algorithms. Furthermore, there is also a need for a responsive design methodology, which can quickly adapt to changes in the requirements during the development process. These demands are stretching the current,largely manual, development process, which is fragmented in the different disciplines and activities concerning modelling, algorithm design, software coding, implementation on the avionics platform and the associated testing at the different stages. The model-based-design (MBD) philosophy presents an attractive solution in addressing the multi-disciplinary nature of the flight algorithm design task. In terms of design process, this materializes in a tight coupling between the modelling, the design and the analysis activities.An integrated design framework for the GNC development for future launcher upper stages has been realized.

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arXiv2018

Model Based Active Slosh Damping Experiment

This paper presents a model based experimental investigation to demonstrate the usefulness of an active damping strategy to manage fluid sloshing motion in spacecraft tanks. The active damping strategy is designed to reduce the degrading impact on maneuvering and pointing performance via a force feedback strategy. Many problems have been encountered until now, such as instability of the closed loop system, excessive consumption in the attitude propellant or problems for engine re-ignition in upper stages. Mostly, they have been addressed in a passive way via the design of baffles and membranes, which on their own have mass and constructive impacts. Active management of propellant motion in launchers and satellites has the potential to increase performance on various levels. This paper demonstrates active slosh management using force feedback for the compensation of the slosh resonances. Force sensors between tank and the carrying structure provide information of the fluid motion via the reaction force. The control system is designed to generate an appropriate acceleration profile that leads to desired attenuation profiles in amplitude, frequency and time. Two robust control design methods, one based on $\mu$ design and the other on parametric structured design based on non-smooth optimization of the worst-case $H_{\infty}$ norm, are applied. The controller is first tested with a computational fluid dynamics simulation in the loop. Finally a water tank mounted on a Hexapod with up to $1100$ liter is used to evaluate the control performance. The paper illustrates that is possible to actively influence sloshing via closed loop.

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arXiv2014

Online placement test based on Item Response Theory and IMS Global standards

This paper aims to present an online placement test. It is based on the Item Response Theory to provide relevant estimates of learner competences. The proposed test is the entry point of our e-Learning system. It gathers the learner response to a set of questions and uses a specific developed algorithm to estimate its level. This algorithm identifies learning gaps, which allows tutors to conceive sequence of courses and remediation adapted to each case of learner, in order to achieve a competence.

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arXiv2013

Multi-Objective Particle Swarm Optimization for Facility Location Problem in Wireless Mesh Networks

Wireless mesh networks have seen a real progress due of their implementation at a low cost. They present one of Next Generation Networks technologies and can serve as home, companies and universities networks. In this paper, we propose and discuss a new multi-objective model for nodes deployment optimization in Multi-Radio Multi-Channel Wireless Mesh Networks. We exploit the trade-off between network cost and the overall network performance. This optimization problem is solved simultaneously by using a meta-heuristic method that returns a non-dominated set of near optimal solutions. A comparative study was driven to evaluate the efficiency of the proposed model.

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arXiv2012

Measures and LMI for space launcher robust control validation

We describe a new temporal verification framework for safety and robustness analysis of nonlinear control laws, our target application being a space launcher vehicle. Robustness analysis, formulated as a nonconvex nonlinear optimization problem on admissible trajectories corresponding to piecewise polynomial dynamics, is relaxed into a convex linear programming problem on measures. This infinite-dimensional problem is then formulated as a generalized moment problem, which allows for a numerical solution via a hierarchy of linear matrix inequality relaxations solved by semidefinite programming. The approach is illustrated on space launcher vehicle benchmark problems, in the presence of closed-loop nonlinearities (saturations and dead-zones) and axis coupling.

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